class_docstr: Decision List Classifier
  
  Currently a slight variant of SkopeRules from skope-rules.
  https://github.com/scikit-learn-contrib/skope-rules
docstr: Provides global explanation for model.
  
  Args:
      name: User-defined explanation name.
  
  Returns:
      An explanation object.
docstr_tok: ["Provides","global","explanation","for","model",".","Args",":","name",":","User-defined","explanation","name",".","Returns",":","An","explanation","object","."]
code: def explain_global(self, name=None):
      """Provides global explanation for model.
  
      Args:
          name: User-defined explanation name.
  
      Returns:
          An explanation object.
      """
  
      check_is_fitted(self, "has_fitted_")
  
      if name is None:
          name = gen_name_from_class(self)
  
      # Extract rules
      rules, prec, recall, feat_rule_map = (
          self.rules_,
          self.prec_,
          self.recall_,
          self.feat_rule_map_,
      )
  
      outcomes = [self.classes_[1]] * (len(self.rules_) - 1)
      # Add the zero case for the default rule
      outcomes.append(self.classes_[0])
      overall_data_dict = {
          "type": "rule",
          "rule": rules,
          "precision": prec,
          "recall": recall,
          "outcome": outcomes,
      }
      data_dicts = [
          {
              "type": "rule",
              "rule": [rules[i] for i in feat_rule_map[feature]],
              "precision": [prec[i] for i in feat_rule_map[feature]],
              "recall": [recall[i] for i in feat_rule_map[feature]],
              "outcome": [outcomes[i] for i in feat_rule_map[feature]],
          }
          for feature in self.feature_names_in_
      ]
  
      internal_obj = {
          "overall": overall_data_dict,
          "specific": data_dicts,
      }
  
      return RulesExplanation(
          "global",
          internal_obj,
          feature_names=self.feature_names_in_,
          feature_types=self.feature_types_in_,
          name=name,
          selector=self.global_selector_,
      )
  
imports: from itertools import count
  from sklearn.base import ClassifierMixin
  from sklearn.utils.validation import check_is_fitted
  from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class, gen_global_selector, gen_local_selector, gen_perf_dicts
  from copy import deepcopy
  import numpy
  import pandas
  import re
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions, typify_classification
  from ..utils._unify_data import unify_data
  import logging
label_desc: Use image node_id 8 for calling the DecisionListClassifier obj's underlying member method code with example usage: obj.explain_global(name) and returns: RulesExplanation